Variable selection in seemingly unrelated regressions with random predictors

David Puelz; P. Richard Hahn; Carlos M. Carvalho

doi:10.1214/17-BA1053

Variable selection in seemingly unrelated regressions with random predictors

David Puelz, P. Richard Hahn, Carlos M. Carvalho

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

This paper considers linear model selection when the response is vectorvalued and the predictors, either all or some, are randomly observed. We propose a new approach that decouples statistical inference from the selection step in a "post-inference model summarization" strategy. We study the impact of predictor uncertainty on the model selection procedure. The method is demonstrated through an application to asset pricing.

Original language	English (US)
Pages (from-to)	969-989
Number of pages	21
Journal	Bayesian Analysis
Volume	12
Issue number	4
DOIs	https://doi.org/10.1214/17-BA1053
State	Published - 2017
Externally published	Yes

Keywords

Decoupling shrinkage and selection
Penalized utility selection
Seemingly unrelated regressions

ASJC Scopus subject areas

Statistics and Probability
Applied Mathematics

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10.1214/17-BA1053

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AB - This paper considers linear model selection when the response is vectorvalued and the predictors, either all or some, are randomly observed. We propose a new approach that decouples statistical inference from the selection step in a "post-inference model summarization" strategy. We study the impact of predictor uncertainty on the model selection procedure. The method is demonstrated through an application to asset pricing.

KW - Decoupling shrinkage and selection

KW - Penalized utility selection

KW - Seemingly unrelated regressions

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Variable selection in seemingly unrelated regressions with random predictors

Abstract

Keywords

ASJC Scopus subject areas

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